Technological advances in computer hardware, software and networking have provided efficient, cost effective computing systems that can communicate with each other from practically anywhere in the world. Such systems are employed to access, browse and search the Internet; compose, send and receive e-mail messages; view and edit documents; transmit and obtain text messages, instant messages, and the like.
Typically, such action can generate massive volumes of data associated with each of the applications employed in information dissemination and authoring; peer-to-peer communication or blogging; and information consumption through web-based instruments such as dedicated search engines, or catalog/product/reservation data warehouses. In addition to generation of data, the data is generally employed dynamically in various automated actions which provide interaction with the user without user intervention. Among such automated features, the following can be found: (i) targeted online advertisement, (ii) alternative product(s) or document(s) recommendation(s), (iii) log records associated with similar online action(s) taken by the user or other users, which can include query completion, or word wheeling, (iv) dynamic generation of web content originated from user queries, and so on.
Generally, the foregoing is supported by automated systems that rely on hierarchical structures of data for decision making, content retrieval, script generation, documentation, and so forth. As the volume of data employed to generate such automated features grow, it becomes necessary to efficiently manage the wealth of information that such automated features rely upon without compromising actual performance (e.g., an optimized engine to generate dynamic content and automate advertisement decisions) as well as perceived performance (e.g., in a sense of quality of service as perceived by a user of an automated feature) of producing such features.